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The Semantic Data Dictionary-An Approach for Describing and Annotating Data

Data Intelligence 2020年第4期2卷 443-486页

作者： Sabbir M.Rashid James P.McCusker Paulo Pinheiro Marcello P.Bax Henrique O.Santos Jeanette A.Stingone Amar K.Das Deborah L.McGuinness Tetherless World Constellation Rensselaer Polytechnic InstituteTroy NY 12180USA School of Information Science Federal University of Minas GeraisBelo Horizonte 31270-901MGBrazil Mailman School of Public Health Columbia UniversityNew York NY 10032USA IBM Research Cambridge MA 02142USA

It is common practice for data providers to include text descriptions for each column when publishing data sets in the form of data dictionaries.While these documents are useful in helping an end-user properly interpret the meaning of a column in a data set,existing data dictionaries typically are not machine-readable and do not follow a common specification standard.We introduce the Semantic Data Dictionary,a specification that formalizes the assignment of a semantic representation of data,enabling standardization and harmonization across diverse data sets.In this paper,we present our Semantic Data Dictionary work in the context of our work with biomedical data;however,the approach can and has been used in a wide range of domains.The rendition of data in this form helps promote improved discovery,interoperability,reuse,traceability,and reproducibility.We present the associated research and describe how the Semantic Data Dictionary can help address existing limitations in the related literature.We discuss our approach,present an example by annotating portions of the publicly available National Health and Nutrition Examination Survey data set,present modeling challenges,and describe the use of this approach in sponsored research,including our work on a large National Institutes of Health(NIH)-funded exposure and health data portal and in the RPI-IBM collaborative Health Empowerment by Analytics,Learning,and Semantics project.

关键词： Semantic Data Dictionary Dictionary mapping codebook Knowledge modeling Data integration Data dictionary Mapping language Metadata standard Semantic Web Semantic ETL FAIR Data

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Hybrid CSI-RS Transmission Mechanism-Based 3D Beamforming Scheme for FDD Massive MIMO System

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China Communications 2016年第S2期13卷 109-119页

作者： Fangchao Zhang Shaohui Sun Qiubin Gao Hui Li School of Electronic and Information Engineering Beihang University State Key Laboratory of Wireless Mobile Communications China Academy of Telecommunications Technology

Massive multiple-input multipleoutput(MIMO) refers to the idea that equipping base station(BS) with a large number of antenna elements,and features the ability of three dimensional(3D) beamforming technique to enable improvement in system performance.The prior works on massive MIMO generally rely on a common assumption of the whole channel characteristics are perfectly known at both user equipment(UE) and BS,however,this is quite difficult to realize in practical frequency division duplexing(FDD) system since the channel state information reference signal(CSIRS) overhead and CSI feedback overhead are proportional to the number of antenna elements.In this paper,two hybrid CSI-RS transmission mechanism-based 3D beamforming schemes are proposed in FDD massive MIMO system,in which non-beamformed CSI-RS configuration is utilized in conjunction with beamformed CSIRS configuration.In the proposed schemes,an angle quantization-based vertical codebook and a DFT-based horizontal codebook are designed,respectively,and an eigenvalue decompositionbased precoding matrix indicator(PMI)selection algorithm is also proposed for CSI acquisition.Simulation results show that the proposed 3D beamforming schemes achieve significant improvement in system capacity without incurring excessive CSI-RS overhead.

关键词： massive MIMO 3D beamforming CSI-RS codebook feedback PMI

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A CSI Acquisition Approach for mm Wave Massive MIMO

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China Communications 2019年第9期16卷 1-14页

作者： Shanzhi Chen Qiubin Gao Runhua Chen Hui Li Shaohui Sun Zhengxuan Liu State Key Lab of Wireless Mobile Communication China Academy of Telecommunication Technology

Massive Multiple-Input Multiple-Output(MIMO)is considered as a key technology for 4G and 5G wireless communication systems to improve spectrum efficiency by supporting large number of concurrent users.In addition,for the target frequency band of 5G system,mmWave band,massive MIMO is pivotal in compensating the high pathloss.In this paper,we investigate the channel state information(CSI)acquisition problem for mmWave massive MIMO.With hybrid analog-digital antenna architecture,how to derive the analog beamforming and digital beamforming is studied.An iterative analog beam acquisition approach is proposed to save system overhead and reduce beam searching complexity.Regarding the digital beamforming,a grouping based codebook is proposed to facilitate CSI feedback.The codebook is then extended to incorporate also analog beam acquisition.Furthermore,channel reciprocity is exploited to save CSI reporting overhead and a two-stage approach is proposed to fully utilize the channel reciprocity at both mobile station and base station side and accelerate the CSI acquisition procedure.

关键词： codebook CSI acquisition hybridbeamforming

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Human Detection for Video Surveillance in Hospital

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Journal of Electronic Science and Technology 2017年第2期15卷 147-152页

作者： Cheng-Hung Chuang Zhen-You Lian Po-Ren Teng Miao-Jen Lin Department of Computer Science and Information Engineering Asia UniversityTaichung 41354 the Psychiatry Department Chang Bing Show Chwan Memofial Hospital Changhua 50544

This paper presents a human detection system in a vision-based hospital surveillance environment. The system is composed of three subsystems, i.e. background segmentation subsystem （BSS）, human feature extraction subsystem （HFES）, and human recognition subsystem （HRS）. The codebook background model is applied in the BSS, the histogram of oriented gradients （HOG） features are used in the HFES, and the support vector machine （SVM） classification is employed in the HRS. By means of the integration of these subsystems, the human detection in a vision-based hospital surveillance environment is performed. Experimental results show that the proposed system can effectively detect most of the people in hospital surveillance video sequences.

关键词： Index Terms--Background segmentation codebook histogram of oriented gradients （HOG） human classification support vector machine （SVM） video surveillance.

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Angle-Based Beamforming in mmWave Massive MIMO Systems with Low Feedback Overhead Using Multi-Pattern codebooks

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China Communications 2019年第9期16卷 18-30页

作者： Yuyan Zhao Yanan Liu Gary Boudreau Akram Bin Sediq Xianbin Wang Department of Electrical and Computer Engineering Western UniversityLondonON N6A 5B9Canada Ericsson Canada OttawaON K2K 2V6Canada

The integration of millimeter-wave(mmWave)communications and massive multiple input multiple output(MIMO)techniques is a promising solution to dramatically increase the 5G network throughput.By using large antenna arrays,beamforming can be adopted to improve the 5G capacity by employing spatial domain resources.In a frequency division duplexing(FDD)based 5G mmWave MIMO system,beamforming operation requires timely downlink channel state information(CSI)feedback.However,the rapid channel variations caused by short wavelength of mmWave band,and the high-level feedback information required due to the large number of antennas in massive MIMO system lead to the significantly increased beamforming overhead.In this paper,by exploiting the higher angular stability of such channels,we propose an angle-based beamforming scheme to reduce the feedback frequency and the number of feedback bits.To facilitate this approach users are initially selected to reduce the intra-zone interference before beamforming.Besides,location related feedback,which is not affected by the number of antennas,is adopted to reduce overhead.The simulation results show that two proposed user selection algorithms can adapt to scenarios with diverse requirements,while the feedback overhead of proposed angle-based beamforming algorithm is sharply reduce compared with that of CSIbased beamforming algorithm.

关键词： angle-based beamforming codebook feedback reduction user selection

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Color Spatial Quantization and Compression Technique Based on Palette

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High Technology Letters 1996年第1期2卷 51-54页

作者：沈丽琴 State Key Laboratory of Local Optical Fiber Communication Networks Shanghai Jiao Tong UniversityShanghai 200052P.R.China

The method of color quantization and the technique of color spatial quantization based onKohonen neural network are presented in this paper.The later is actually a method of matrixquantization.Using Kohonen NN a palette and a codebook for color spatial quantization canbe easily obtained.Image compression techniques for digital areonautical maps must be cho-sen to allow rapid decompression and display while maximizing the compression ratio and im-age quality.The palette-based compression technique uses a palette and a codebook based onpalette for color spatial quantization as double look-up -tables,making image decompressionand display just a quick and simple process of looking up the two tables.

关键词： Kohonen neural network Palette codebook Color spatial quantization Compression

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A codebook Design Method for Robust VQ-Based Face Recognition Algorithm

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Journal of Software Engineering and Applications 2010年第2期3卷 119-124页

作者： Qiu Chen Koji Kotani Feifei Lee Tadahiro Ohmi 不详

In this paper, we present a theoretical codebook design method for VQ-based fast face recognition algorithm to im-prove recognition accuracy. Based on the systematic analysis and classification of code patterns, firstly we theoretically create a systematically organized codebook. Combined with another codebook created by Kohonen’s Self-Organizing Maps (SOM) method, an optimized codebook consisted of 2×2 codevectors for facial images is generated. Experimental results show face recognition using such a codebook is more efficient than the codebook consisted of 4×4 codevector used in conventional algorithm. The highest average recognition rate of 98.6% is obtained for 40 persons’ 400 images of publicly available face database of AT&T Laboratories Cambridge containing variations in lighting, posing, and expressions. A table look-up (TLU) method is also proposed for the speed up of the recognition processing. By applying this method in the quantization step, the total recognition processing time achieves only 28 msec, enabling real-time face recognition.

关键词： Face Recognition Vector Quantization (VQ) codebook Design Code Classification Histogram Method

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基于改进的codebook算法的车轮轮廓提取

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内蒙古农业大学学报（自然科学版） 2014年第1期35卷 103-107页

作者：殷刚内蒙古化工职业学院测控与机电工程系呼和浩特010070

提取车轮轮廓在机动车车型识别课题中有重要作用,通过检测侧面图像车辆的车轮数便可确定被测车辆的轴数,为车型的识别提供重要的底盘信息。本文提出了一种鲁棒性较强的车轮轮廓提取方法,通过摄像机拍摄道路行驶车辆的侧面视频,利用改进... 详细信息

提取车轮轮廓在机动车车型识别课题中有重要作用,通过检测侧面图像车辆的车轮数便可确定被测车辆的轴数,为车型的识别提供重要的底盘信息。本文提出了一种鲁棒性较强的车轮轮廓提取方法,通过摄像机拍摄道路行驶车辆的侧面视频,利用改进后的codebook算法提取出目标车辆后,经圆形度初步筛选近似为圆形的目标,再通过Hough变换圆检测来验证圆,最后完成车轮轮廓的提取。

关键词： codebook 圆形度圆检测轮廓提取

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Fall detection system in enclosed environments based on single Gaussian model

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Journal of Measurement Science and Instrumentation 2012年第2期3卷 123-128页

作者： Adel Rhuma Jonathon A Chambers Advanced Signal Processing Group Dept.of Electronic and Electrical EngineeringLoughborough UniversityLoughborough

In this paper,we propose an efficient fall detection system in enclosed environments based on single Gaussian model using the maximum likelihood method.Online video clips are used to extract the features from two cameras.After the model is constructed,a threshold is set,and the probability for an incoming sample under the single Gaussian model is compared with that threshold to make a decision.Experimental results show that if a proper threshold is set,a good recognition rate for fall activities can be achieved.

关键词： humans fall detection enclosed environments one class support vector machine(OCSVM) imperfect training data shape analysis maximum likelihood(ML) background subtraction codebook voxel person

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Towards an Efficient Hierarchical codebooks for Content-Based Images Retrieval

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Journal of Electronic Science and Technology 2014年第1期12卷 107-111页

作者： Z.Elleuch K.Marzouki the Informatics for Industrial Systems Lab the Higher Institute of Applied Sciences and Technology of Sousse the Higher Institute of Applied Sciences and Technology of Sousse

In space feature quantization, the most important problem is designing an efficient and compact codebook. The hierarchical clustering approach successfully solves the problem of quantifying the feature space in a large vocabulary size. In this paper we propose to use a tree structure of hierarchical self-organizing-map （H-SOM） with the depth length equal to two and a high size of branch factors （50, 100, 200, 400, and 500）. Moreover, an incremental learning process of H-SOM is used to overcome the problem of the curse of the dimensionafity of space. The method is evaluated on three public datasets. Results exceed the current state-of-art retrieval performance on Kentucky and Oxford5k dataset. However, it is with less performance on the Holidays dataset. The experiment results indicate that the proposed tree structure shows significant improvement with a large number of branch factors.

关键词： codebook content-based imageretrieval incremental learning self-organizing-map.

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